Data Engineer (Spark, Azure)

We are looking for a Data Engineer who will take a leading role in designing and implementing a scalable enterprise search engine - a platform that provides stakeholders with an intuitive, efficient, and reliable way to query and explore the firm’s data landscape.
Our client is a leading global financial services firm providing wealth management, investment banking, and asset management services to clients worldwide.
This is a hybrid role requiring presence in the client's office in Krakow 3 days a week, with flexible working hours.
Responsibilities
Design, build, and optimize an internal data search engine
Analyze datasets and metadata to improve searchability, indexing, and relevance
Gather and refine search and data discovery requirements with business and IT stakeholders
Translate business needs into technical specifications and support Agile delivery
Ensure integration with the broader data ecosystem (data, platform, analytics teams)
Support testing and monitor search performance, accuracy, and usability
Prepare analytical reports on data availability and search effectiveness
Requirements
3 years + of experience as a Data Engineer, including exposure to large-scale or Big Data environments
Strong experience with SQL and database systems (relational and NoSQL), including query optimization and schema design
Strong programming skills in Python and Spark
Experience with Azure cloud services, including Azure Databricks, Data Lake, and Azure Data Factory, would be beneficial
Strong communication and stakeholder management skills, with the ability to translate search-related needs into technical solutions